Making statistics more sustainable
The GSS Statistics course is the first time GSS students have a closer contact with the subject and is an important step in their education. Despite the importance of the topic, the course did not have significant changes for a long time. Therefore, the aim of this project was to re-design the statistics course, making it more attractive to students and better aligned to sustainability science.
Background
The Statistics GSS course is a basic obligatory course for all GSS students. Statistics play indeed a key role in virtually all branches of science. The many uses of statistics, e.g. for testing experiments and predicting trends, are broadly applied in sustainability science. After one year teaching the course, two main points for improvement were identified: (i) transition from SPSS statistical software to R; and (ii) re-design of lectures, assignments and practicals, e.g. through the inclusion of sustainability-related datasets and examples. The first point (i) is important because R is a widely used open software which allows high reproducibility of statistical analyses. Besides, there is a large academic community working and building (open) knowledge in R. As SPSS is a paid private software which is not being so much used nowadays, the change to R can represent a benefit to students and also a better alignment with university principles of Open and Fair data. The second point (ii) is a great addition because the inclusion of examples related to sustainability can increase the interest and intrinsic motivation of students. Research shows that intrinsic motivation is a better approach than external motivation to help students to learn faster as well as acquire long-term and deeper knowledge.
Project description
The re-design of the Statistics course involved:
- Re-design of the lectures. The lectures were re-designed to include examples linked to sustainability and examples using the software R.
- Re-design of the practicals. A new reader was produced using examples in R and a combination of socio-ecological variables that are analyzed throughout the practicals. Part of the codes are provided in the reader, however, other codes need to be developed by students based on instructions and exercises.
- Re-design of the assignment. The assignment was re-designed to include diverse datasets and examples using the software R. The datasets are now based on real data from selected papers and cover topics such as carbon sequestration, biomass, litter decomposition, green roofs and habitat heterogeneity. The use of realistic, modern and sustainability-related datasets can increase the internal motivation of students. The structure of the assignments were modified to explore higher levels of learning (based on Bloom`s Taxonomy).
- Re-design of the exams. New exam questions using R language and output were developed.
The links to sustainability were highlighted throughout all aspects of the course. This helps students and teachers to get more motivated and can also provide students a more concrete and less abstract idea on how they can use statistics in the future.
Aims
The aim of this proposal is to re-design the whole course, focusing on (i) elaborating datasets and examples linked to sustainability science, (ii) starting to use R as the main statistical software and (iii) renovating the format of the practicals. The re-design of practicals and lectures will hopefully better engage students, by showing them how statistics can be useful in sustainability science in a more interactive and practical way. The new format will also provide students access to state-of-the-art methods, and new skills (e.g. programming) that are crucial nowadays. Furthermore, with the change to R, the project may contribute to more open, inclusive, collaborative and transparent science.
Results
The aim of this proposal was to re-design the whole course, focusing on (i) elaborating datasets and examples linked to sustainability science, (ii) starting to use R as the main statistical software and (iii) renovating the format of the practicals. The re-design of practicals and lectures was useful to better engage students, by showing them how statistics can be useful in sustainability science in a more interactive and practical way. The new format also provided students access to state-of-the-art methods, and new skills (e.g. programming) that are crucial nowadays. Furthermore, with the change to R, the project contributes to more open, inclusive, collaborative and transparent science.
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